Philip Hodgetts’ unique blend of business and production knowledge gives him insight into the current state of the industry, and a remarkably accurate look forward. Here he shares his thinking, and points to articles of interest from other sites, with context as to why they're interesting.

What Do We Want Machine Learning to be Used for in Post?

As someone who’s watched the development of machine learning, and who is in the business of providing tools for post production workflows that “take the boring out of post” you’d think I’d be full of ideas of how post can be enhanced by machine learning.

I’m not.

There are some very obvious ways to use machine learning that I group under Cognitive Services. These are the services that multiple vendors provide, such as speech-to-text, Natural Language Processing (keyword, concept, entity and emotion extraction), Facial Detection and Recognition, Image recognition and keyword extraction, et. al.

I also acknowledge that many people won’t be entirely comfortable with auto generated keywords and logging, and I’m fine with that. Ultimately the majority of people will take advantage of any automated help they can.

These are obvious and I can’t imagine the NLE of the future won’t include visual search and speech search by default, and probably keyword and concept extraction (and the rest). But beyond that…?

Sure, that’s a lot, but in other areas of programming we’re seeing machine learning being applied in many different ways, but nothing I can see that would enhance the post process.

We do have one idea that we may use in Lumberjack Builder (that I won’t reveal right now for competitive reasons) but it’s a very basic functionality that would (if successful) automate a process that currently would require manual input.

Beyond that, I am puzzled as to what workflow step we might automate. What recurrent activities might be recognized and helped? What user behavior could be modeled to enhance the app? Hopefully your imaginations are more open than mine.